tbuckley/cabot-search huggingface dataset:
Abstract 14107: Virtual Cardiac Point-of-Care Ultrasound Curriculum Among Residents: A Medical Education Project
Authors: Arpanjeet Kaur, Yoni Balboul, Kruti Gandhi, Adam Rothman
Journal: Circulation (2022)

INTRODUCTION: Point-of-care ultrasound (POCUS) is becoming increasingly important for rapid assessment and diagnosis in a variety of clinical situations. With the ongoing COVID-19 pandemic, the aim of this study is to determine whether a virtual POCUS session can improve learner competency in assessing left ventricular (LV) systolic function. METHODS: An hour long session, involving a short lecture and fourteen practice questions was created. The questions consisted of cardiac ultrasound clips from real patients, evaluated by three POCUS experts. For each clip, LV systolic function was classified as hyperdynamic, normal, reduced, or severely reduced. The session was given separately to a group of interns (n1=30) and a group of senior residents (n2=39) virtually via Zoom. Series of clips were shown as the lecture progressed and participants recorded their answers as either hyperdynamic, normal, reduced, or severely reduced using the polling feature within the Zoom platform. Effect size as the percent of correct responses was calculated. Data was analyzed using SPSS software with independent t-test and paired t-test analysis with a level of statistical significance as p ≤0.05. Results: The intern group had a mean score of 69.9% [SD 21.8%] and the resident group had a mean score of 74.2% [SD 21.5%]. All participants achieved a mean score of 66.6% [SD 26.0%] during the first half of the lecture, which then improved to 77.6% [SD 14.2%] in the second half [p value 0.547]. Both groups showed similar overall trends, although these were not statistically significant. When combined, extremes of LV function (hyperdynamic and severely reduced) were better recognized than more subtle differences (reduced and normal) [81.4%±18.1 vs 55.2±15.9; p = 0.001] overall. Conclusion: Compared to the conventional in-person approach, this study highlights the potential for virtual didactic sessions in POCUS training with impressive results when recognizing extreme cardiac findings.
Abstract 14044: Leveraging Multi-Omics to Identify Biologically-Informed Clusters of Individuals With Differing Underlying Disease Risk Mechanisms Using an Innovative Network Modelling Approach
Authors: Minoo Bagheri Naraghi, Bertrand De Meulder, Jeffrey Annis, Evan Brittain, Jonathan Mosley, Jane F Ferguson
Journal: Circulation (2022)

Background: The rates of known cardiometabolic risk elevation are highly variable among patients suggesting that there are other risk mediators underlying diseases. We hypothesized that using cutting-edge and innovative multi-omics integrative network analysis in conjunction with the consensus clustering approach would identify clusters of individuals which may represent novel functional and/or pathophysiological risk mechanisms of cardiometabolic disorders. Methods: The genetically predicted levels of metabolites and proteins constructed from the GWAS data of Framingham/Malmö and KORA-TWINS were imputed in 13,562 BioVU participants. These 2 layers of omics data were integrated using similarity network fusion in conjunction with consensus clustering approaches. The identified clusters of individuals were tested for associations with 14 cardiometabolic diseases using logistic regression adjusting for known risk factors to identify endotypic determinants of diseases. Pathway analysis comparing each cluster to the rest of participants was performed using Reactome and MetaboAnalyst. Results: We identified 5 clusters across which LDL-C was significantly (p=0.001) different. The significant associations were found for cluster 1 with coronary artery disease (p=0.04), cluster 2 with cardiomyopathy(p=0.004) and atrial fibrillation (p=0.03) and cluster 4 with congenital heart disease (p=0.03) [ Fig 1 ]. Thus, clusters 1, 2 and 4 are endotypic determinants of the above diseases. Each of these clusters was associated with distinct pathways indicating candidate mechanisms of diseases related to the clusters. Conclusions: This novel discovery-oriented multi-omics clustering method identified biologically-related subgroups of individuals and revealed novel risk mechanism and biomarkers of cardiometabolic diseases. The innovative network-based models advance precision medicine by enabling future prognostic risk prediction tools.
Abstract 14756: Outcomes of Cardiac Co-Morbidities in Renal Transplantation: A National Population-Based Cohort Study
Authors: Bilal Hussain, Vivek Kasinath, Reza Abdi, Timir K Paul
Journal: Circulation (2022)

Background Cardiovascular disease (CVD) is common and associated with higher mortality in end-stage renal disease patients, but its impact on mortality from renal transplantation has not been studied formally. Our aim was to investigate the impact of CVD on the mortality of renal transplant recipients at the time of transplantation. Methods The National Inpatient Sample 2016-2019 was analyzed to identify a patient cohort admitted for renal transplantation with a diagnosis of a cardiovascular diseases using ICD-10 codes. The prevalence of various cardiac co-morbidities and their effect on mortality in renal transplant recipients were evaluated. A multivariate logistic regression model was used to analyze the in-hospital mortality rates. Results Analysis of 142,333,352 patients revealed that 84,525 (0.059%) were admitted for renal transplantation, of whom 32.5% had cardiac co-morbidities. Mean age of these patients was 57 years, and 66% were males. 19% of these patients had ischemic heart disease, 15.9% had heart block, 8.1% had heart failure, 7.1% had atrial fibrillation, 7.6% had congenital heart disease (CHD), 3.4% had pulmonary hypertension, 2.7% had ventricular arrhythmia, 2.5% had non-rheumatic valvular heart disease (NRVHD), 1.3% had chronic rheumatic heart disease (CRHD), 0.05% had pericarditis, and 0.018% had infective endocarditis. In patients undergoing renal transplant, CVD was associated with more than four times higher likelihood of mortality (OR 4.77, CI 2.84-8.03, p=0.00). Pericarditis (OR 31.56), ventricular arrhythmia (OR 13.9), heart failure (OR 5.4), heart block (OR 5.0), atrial fibrillation (OR 2.64), pulmonary hypertension (OR 2.54), and ischemic heart disease (OR 1.7) were also associated with significantly higher mortality (p&lt;0.05). CHD, NRVHD, CRHD, and infective endocarditis had no significant association with mortality. Conclusions The prevalence of CVD in renal transplant recipients is 32.5%, and it is associated with over four-fold higher odds of mortality. Other cardiac co-morbidities associated with increased mortality following renal transplantation are ischemic heart disease, heart failure, atrial fibrillation, ventricular arrhythmia, heart block, pericarditis, and pulmonary hypertension
Abstract 12739: Evaluation of Quantitative Decision-Making for Rhythm-Management of Atrial Fibrillation Using Tabular Q-Learning
Authors: Christopher Barrett, Yuto Suzuki, Sundous Hussein, LUKASZ CERBIN, Syed Rafay Ali Sabzwari, Lohit Garg, Alexis Tumolo, Amneet Sandhu, John West, Matthew Zipse, Ryan G Aleong, Paul D Varosy, Farnoush Banaei-Kashani, Wendy Tzou, Michael Rosenberg
Journal: Circulation (2022)

Introduction: Rhythm-management is among the most complex decisions for patients diagnosed with atrial fibrillation (AF). While clinical trials have identified subsets of patients who might have a benefit from a given rhythm-management strategy, for individual patients it is not always clear which strategy is expected to have the greatest mortality benefit or durability. Hypothesis: Combined application of unsupervised machine learning and reinforcement learning can assist with optimizing individualized treatment strategies for patients with AF. Methods: In this investigation of over 50K subjects with a new AF diagnosis between the dates of October 11, 2010 and October 26, 2020, we examined the application of a type of artificial intelligence called tabular Q-learning to identify the optimal initial rhythm-management strategy, based on a composite outcome of mortality, change in treatment, and sustainability of the given treatment, termed the reward function. Results: We first applied an unsupervised learning algorithm using a variational autoencoder with K-means clustering to cluster AF patients into 8 distinct phenotypes, which matched what has been observed in clinical practice. We then fit a Q-learning algorithm to predict the best outcome for each cluster, in which we found that while a rate-control strategy was most frequently selected by treating providers, the outcome was superior for rhythm-control strategies across all cluster groups, with those subjects in whom provider-selected treatment matched what the Q table recommended having fewer total deaths [4 (8.5%) vs 473 (22.4%), Odds ratio = 0.32, P = 0.02] and a greater reward [-0.0115±0.26 vs -0.392±2.06, P = 4.8x10 -6 ]. We then demonstrated application of dynamic learning by updating the Q table prospectively using batch gradient descent, in which the optimal strategy in some clusters changed from cardioversion to ablation, although the reward was greatest when the largest amount of data was used for model fitting. Conclusions: We found that tabular Q-learning provides a dynamic and interpretable approach to apply artificial intelligence to clinical decision making for AF. Further work is needed to examine application of Q-learning prospectively in clinical patients.
Abstract 14422: Mitochondrial ROS Scavenger JP4-039 Improves Mitochondrial Oxidative Phosphorylation and Induces Angiogenesis in Murine and Human Coronary Artery and Atrial Endothelial Cells
Authors: Rayane Brinck Teixeira, Michelle King, Taslova Abedin, Catherine Karbasiafshar, Sidharth Raj, Aja Tucker, Mohamed Sabra, Madigan Stanley, Peng Zhang, Peter Wipf, Frank W Sellke, Ruhul Abid
Journal: Circulation (2022)

Introduction: Reducing mitochondrial ROS (mito-ROS) has been a therapeutic goal to improve cardiovascular disease. Here, we evaluated the effects of mito-ROS scavenger JP4-039 with a focus on mouse heart and human coronary artery endothelial cell (MHEC, HCAEC). Hypothesis: We hypothesized that JP4-039 would improve oxidative phosphorylation (OXPHOS) in EC and induce angiogenesis in post-AMI (acute myocardial infarction) hearts. Methods: Human atrial explants, NOX2-overexpressing (OE) MHEC, and HCAEC were treated with 1-5μM JP4-039 and examined for sprouting, tube formation, mitochondrial complex expression (Western blot), and OXPHOS measurements (Seahorse). FVB mice (n=8/group) underwent AMI surgery and were assigned to vehicle (sunflower seed oil) or JP4-039 group (1mg/kg, i.p., 3x/week for 4 weeks). Left ventricle (LV) function and capillary density in infarcted LV were assessed by echocardiogram and immunofluorescence, respectively, 28 days after AMI. Data were analyzed by One-way ANOVA and Tukey’s post-hoc, or student’s t test, as appropriate. A p-value &lt;0.05 was considered statistically significant. Results: HCAEC treated with JP4-039 showed significantly increased expression of mitochondrial complex I (0.7±0.1 vs. 1.1±0.1) and V (1.0±0.1 vs. 1.2±0.1) with corresponding increase in basal (19.8±0.4 vs. 23.0±1.0) and maximal respiration (31.2±1.6 vs. 56.0±2.6), ATP production (16.6±0.3 vs. 18.5±0.4) and spare respiratory capacity (11.3±1.6 vs. 33.0±2.9) as compared with vehicle-treated cells. JP4-039 increased tube formation in NOX2-OE MHEC (12.6±2.2 vs. 21.3±2.4 tubes), HCAEC (33.6±3.1 vs. 49.0±2.6) as well as EC sprouting in mouse atrium (4496±1857 vs. 19552±4352 pixel 2 ). In post-AMI animals, JP4-039 improved LV systolic function (EF 24.4±3.6 vs 41.3±5.2%) and capillary density (451.7 (379.9; 629.7) vs. 698.3 (503.6; 965.8) capillaries/mm 2 ) in vivo . Conclusions: JP4-039 improved OXPHOS in ECs in vitro, and induced coronary angiogenesis in post-AMI hearts in vivo and in atrial tissues ex vivo . These findings were associated with improved cardiac function in post-AMI animals, suggesting that a mito-ROS scavenger may have significant roles in coronary angiogenesis in ischemic myocardium.
Abstract 14305: Long-Term Results of Left Atrial Ganglionated Plexi Ablation in Patients With Syncope and POTS
Authors: Mithilesh Das, Awaneesh Kumar, Nektarios Vasilottos
Journal: Circulation (2022)

Background: Cardioneuroablation (CNA) of atrial ganglionated plexi (GP) using radiofrequency anergy has shown to be effective in treating refractory neurocardiogenic syncope (NS) during a short-term follow-up. However, there is no study of CNA in patients with postural orthostatic tachycardia syndrome (POTS) with syncope. Methods: Eight patients (mean age 39+9 years, male: 62%) with treatment-refractory (NS: 4, POTS: 4) syncope underwent CNA of all 4 GPs of the left atrium and followed for 35 + 10 months. Results: All patients were non-responders to lifestyle modification and multiple drug therapies including (fludrocortisone, midodrine, beta-blockers, clonidine and pyridostigmine). Syncope recurred only in 3 (37.5%) patients after a mean duration of 34.9 + 15 months. Syncope recurred in 2 of 4 (50%) patients with NS and in 1 of 4 (25%) patients with POTS. Conclusions: Contrary to prior publications, syncope recurs in 37.5% patients during long-term follow up after CAN in both POTS and NS patients.
Abstract 13992: Antiplatelet Therapy Reduces Mortality When Compared to Direct Oral Anticoagulants in Post-Transcatheter Aortic Valve Replacement Patients Without Any Indication for Anticoagulation
Authors: Matheus Jose Barbosa Moreira, Natália Araujo do Amaral Peixoto, Ofonime Chantal Udoma Udofa, Silvia de Lucena Silva Araujo, Shirley Tinajero
Journal: Circulation (2022)

Introduction: Transcatheter Aortic Valve Replacement (TAVR) is a widely used minimally invasive treatment for severe aortic stenosis. Though the procedure is safe and effective, patients are still at risk for ischemic and hemorrhagic events after this intervention. The post-procedure antithrombotic management in these patients continues to be a source of debate, particularly in patients who do not have a preexisting or concurrent comorbidity which requires long-term anticoagulation therapy. Methods: We performed a systematic review and meta-analysis to compare Direct Oral Anticoagulants (DOACs) versus antiplatelet therapy after TAVR in patients without previous indication for chronic oral anticoagulation. PubMed, EMBASE, and Cochrane databases were searched for randomized controlled trials (RCTs). Risk ratio (RR) with P value &lt; 0.05 were considered statistically significant. The primary endpoints of interest were death, obstructive valve thrombosis and major bleeding. No time for follow-up was limited. Results: Three studies involving 2922 patients undergoing TAVR were included. Of the participants, 1459 received antiplatelets and 1463 received DOACs. Antiplatelets were associated with significantly lower all-cause mortality (RR 1.68 [1.22-2.30], 95%IC; p=0.001). Major bleeding did not differ significantly between groups, but DOACs had a higher risk of bleeding when compared to antiplatelet drugs (RR 1.44 [0.90-2.32]; 95%IC, p=0.13). The antiplatelet group had a significantly higher risk of valve thrombosis than the DOACs group (RR 0.27 [0.14-0.51]; 95%IC; p&lt;0.0001). Conclusions: This meta-analysis suggests that the use of antiplatelet, in comparison to the DOACs, after the TAVR procedure, reduces all-cause mortality, without significantly increasing the risk of bleeding. However, DOACs have been shown to reduce valve thrombosis. This is the best current evidence available. More RCTs, however, are needed to consolidate these findings.
Abstract 12868: Real-Time Explainable Detection of Stenosis in Coronary Angiography
Authors: Keith A Dufendach, Emma Erickson, Cecilia Morales Garza, Robert Edman, David Kaczorowski, Artur Dubrawski
Journal: Circulation (2022)

Background: Coronary angiography is the gold standard for evaluating coronary artery disease and determining the appropriate treatment strategy for a patient. The aim of this study is to use a machine learning (ML)-based object detection algorithm to identify images with clinically significant stenoses and provide explainable output by localizing the area of stenosis within each image. Methods: We utilize the YOLOv5 object detection algorithm to detect clinically significant stenoses by treating narrowing of the vessel as the object to be located in an image. Models are trained utilizing a 5-fold cross-validation strategy on a dataset consisting of the middle frame from 756 randomly selected cine clips from an interventional cardiology suite. Maximum object confidence on the validation dataset is used for downstream whole image classification. Results: Across 5 folds, mean bounding box precision was 0.342 ± 0.074 and recall was 0.305 ± 0.021 at an intersection over union threshold of 0.6. The image classification model achieved a mean and standard deviation area under the receiver operating characteristic curve of 0.863 ± 0.042 with a mean accuracy of 0.809 ± 0.041 at the optimal confidence cutoff of 0.283 ± 0.241. Additionally, trained model predictions occurred at a rate of 32.8 ± 3.6 frames per second, allowing for live model inference and provider support at a standard angiographic frame rate of 15 frames per second. Conclusions: The proposed object detection ML approach is a time-efficient and data-efficient method of diagnosing significant coronary artery stenosis. These results combine state-of-the-art performance in detecting stenosis in angiographic images with improved explainability over single-step classification with a deep neural network.
Abstract 13978: Biologic versus Imaging Markers Predicting Readmission and Death in Heart Failure With Preserved Ejection Fraction
Authors: Aaron J Wengrofsky, Ushma V Majmudar, Matthew Atienza, Francesco Castagna, Waqas Hanif, Mario J Garcia
Journal: Circulation (2022)

Introduction: Increased B-type Natriuretic Peptide (NT-proBNP) levels have been associated with adverse outcomes in patients with heart failure with preserved ejection fraction (HFpEF). Global longitudinal strain (GLS) and wall stress (WS) are frequently reported to be abnormal in these patients as well, but studies examining how structural changes in those with HFpEF affect morbidity and mortality have been scarce. Hypothesis: NT-proBNP is a stronger predictor of death and heart failure readmissions in HFpEF patients when compared to GLS and WS. Methods: We conducted a retrospective study of 237 patients admitted with acute decompensated heart failure, all with EF &gt; 50. Average age was 78 + 11, 69% of patients were female, and average BMI was 29 + 13. GLS was measured using speckled tracing echocardiography and WS was calculated from systolic blood pressure, end-systolic left ventricular (LV) dimension, and end-systolic posterior wall thickness. Results: During a follow-up period of 2 years, 55 patients died and 55 were readmitted with the diagnosis of acute decompensated heart failure. Mean NT-proBNP among all patients was 9982 + 16268, mean GLS -17.84 + 4.52, and mean WS was 52.27 + 25.23. 129 patients had an abnormal or borderline GLS of &gt;-18, whereas nearly all patients (230) had an abnormal WS of &lt;109. (See table for results.) Conclusion: GLS and WS are reduced in a significant proportion of HFpEF patients. However, our data suggests that compared to echocardiographic indices of LV systolic function, biomarkers have a stronger short-term prognostic value.
Abstract 13703: Sex Differences on Cardiovascular Outcomes of Pcsk9-Inhibitors: A Meta-Analysis
Authors: Frederick B Rivera, Deogracias V De Luna, Marie Francesca M Ansay, Aubrey Melody Rocimo, Pia Gabrielle I Alfonso, Bradley Ashley Ong, Jem Marie P Golbin, Nishant Shah, Annabelle Santos Volgman
Journal: Circulation (2022)

Background: LDL-Cholesterol (LDLC) lowering therapies have been proven to significantly lower major adverse cardiovascular events (MACE) in patients with cardiovascular disease. Ideal LDL-C target levels are often not achieved using a high-dose statin and ezetimibe. The proprotein convertase subtilisin/kexin type-9 (PCSK-9) inhibitors can further reduce LDL-C and MACE, yet gender differences in LDL-C reduction remains unclear. We sought to determine if there are sex differences in efficacy outcomes of PCSK-9 inhibitors. Method: A comprehensive literature search was performed, and ongoing studies were identified using ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform. We used a PRISMA, Preferred Reporting Items for a Review and Meta-analysis and RevMan version 5.4 software to conduct a meta-analysis, heterogeneity test, and sensitivity analysis on the included studies. We established the significance level for all outcomes at a P-value of &lt;0.05. Statistical heterogeneity was identified through forest plots and a standard Chi-squared test with a significant level of p&lt;0.1. The extent of heterogeneity was based on the I 2 statistic, wherein a value of more than 50% was interpreted as substantial heterogeneity. Fixed-effects analysis was applied in this meta-analysis. Results: There was a significant reduction in MACE in PCSK9 inhibitor arm vs. placebo in both males (HR 0.85, 95% CI 0.80 to 0.91, p&lt;0.0001, and females (HR 0.86, 95% CI 0.76 to 0.96, p=0.009) (Figure). Furthermore, there was a similar significant reduction in LDLC with PCSK-9 inhibitors compared to placebo and ezetimibe for both sexes. Lastly, there was a significant reduction in LDL-C seen in both sexes when analyzed as to the frequency of PCSK9 inhibitor administration and the type of PCSK9 inhibitor given. Conclusion: This meta-analysis found no sex differences and similar efficacy in women and men in reducing MACE using PCSK-9 inhibitors.
Abstract 13153: Proteomic Differences in Sarcomere Positive HCM May Explain More Severe Clinical Differences
Authors: Ramin Garmany, Johan M Bos, David J Tester, John Giudicessi, Cristobal Dos Remedios, Surendra Dasari, Kenneth L Johnson, Zachary C Ryan, Joseph J Maleszewski, Steve R Ommen, Joseph A Dearani, Michael J Ackerman
Journal: Circulation (2022)

Introduction: Hypertrophic cardiomyopathy (HCM) is characterized by left ventricular hypertrophy. Approximately 40-50% of HCM is caused by pathogenic variants in genes encoding proteins of the cardiac sarcomere. Patients with sarcomeric HCM have earlier expression and more severe disease progression. Herein, we evaluated the proteomic differences between patients with sarcomeric HCM and genotype negative HCM. Methods: Mass-spectrometry was performed on cardiac tissue from genotyped patients with HCM obtained after surgical myectomy, followed by differential proteomics (log2fc ≥